Modeling and Detection of Joint Loosening using Output-Only Broad-Band Vibration Data

Damage detection and structural health monitoring techniques based on vibration data have seen increased attention in recent years. Among the different vibration-based methods, the ones based on random vibrations are of particularly interest, especially when they do not require measurement of the input(s). In this work, several frequency and time domain signal processing techniques are explored in their respective abilities to detect damage in a bolted composite structure. First, a joint loosening model is developed and used to simulate the dynamic response to a stationary Gaussian excitation. Informed by the model, two signal processing techniques are used to assess the connection strength. The first method relies on basic statistical properties of the measured strains and their time derivatives, while the second is based on the signal power in different frequency bands. Both approaches are then used to assess progressive bolt loosening on an experimental composite-to-metal joint. All strain response data were obtained using a fiber optic strain sensing system. Results are presented in the form of Receiver Operating Characteristic (ROC) curves, showing both Type-I and Type-II errors associated with the proposed detection schemes.